Ensuring software quality in open⁃source environments requires adaptive mechanisms to enhance scalability,optimize service provisioning,and improve reliability.This study presents the dynamic correlation analysis tech...Ensuring software quality in open⁃source environments requires adaptive mechanisms to enhance scalability,optimize service provisioning,and improve reliability.This study presents the dynamic correlation analysis technique to enhance software quality management in open⁃source environments by addressing dynamic scalability,adaptive service provisioning,and software reliability.The proposed methodology integrates a scalability metric,an optimized service provisioning model,and a weighted entropy⁃based reliability assessment to systematically improve key performance parameters.Experimental evaluation conducted on multiple open⁃source software(OSS)versions demonstrates significant improvements:scalability increased by 27.5%,service provisioning time reduced by 18.3%,and software reliability improved by 22.1%compared to baseline methods.A comparative analysis with prior works further highlights the effectiveness of this approach in ensuring adaptability,efficiency,and resilience in dynamic software ecosystems.Future work will focus on real⁃time monitoring and AI⁃driven adaptive provisioning to further enhance software quality management.展开更多
BACKGROUND Psychological comorbidities,such as anxiety and depression,in patients with chronic ankle instability(CAI)may impede ankle function improvement,although the precise nature of this association warrants furth...BACKGROUND Psychological comorbidities,such as anxiety and depression,in patients with chronic ankle instability(CAI)may impede ankle function improvement,although the precise nature of this association warrants further investigation.AIM To analyze the correlation of anxiety and depression with ankle function in patients with CAI and discussing the risk factors.METHODS This study included 116 patients with CAI,who were admitted to our hospital from July 2022 to July 2024.Anxiety and depression states of patients were assessed with the self-rating anxiety scale(SAS)and self-rating depression scale(SDS),respectively,and their ankle joint function was assessed with the anklehindfoot function score of the American Orthopedic Foot and Ankle Society.Further,the ankle function of patients with CAI with different anxiety and depression states was discussed.Furthermore,the Pearson correlation coefficient was used to analyze the correlation of anxiety and depression with ankle joint function in such patients.Univariate and multivariate analyses were conducted to investigate the factors affecting ankle joint function in patients with CAI.RESULTS Among the 116 patients with CAI,97,13,5,and 1 cases demonstrated none,mild,moderate,and severe anxiety,whereas 95,15,6,and 0 cases showed none,mild,moderate,and severe depression,respectively.The average ankle joint function score was 74.82±6.93 points.The ankle joint function in patients with CAI presented a significant downward tendency as the degree of anxiety and depression increased.Correlation analysis revealed that both the SAS and SDS scores of patients with CAI were significantly negatively correlated with the ankle joint function score.Univariate and multivariate analyses indicated that the risk factors affecting patients’ankle joint function included early functional rehabilitation,visual analog scale,and SDS.CONCLUSION A substantial number of patients with CAI suffer from anxiety and depression,and these negative emotions,to a certain extent,harm the smooth rehabilitation of ankle joint function.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimat...Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.展开更多
Objective:To analyze the correlation between perceived stress,job burnout,and subjective well-being among undergraduate nursing interns.Methods:A total of 260 clinical nursing interns who interned in tertiary hospital...Objective:To analyze the correlation between perceived stress,job burnout,and subjective well-being among undergraduate nursing interns.Methods:A total of 260 clinical nursing interns who interned in tertiary hospitals from July 2024 to April 2025 were selected as the survey subjects.They were administered the Chinese version of the Perceived Stress Scale(CPSS),the Maslach Burnout Inventory-Human Services Survey(MBI-HSS),and the General Well-being Schedule(GWB)to evaluate the correlation between perceived stress,job burnout,and subjective well-being.Results:The subjective well-being scores of those with higher perceived stress were lower than those with moderate stress;individuals with severe job burnout had lower subjective well-being compared to those without job burnout or with mild to moderate job burnout levels(p<0.05).Correlation analysis revealed that the subjective well-being of undergraduate nursing interns was negatively correlated with perceived stress and job burnout(p<0.05).Conclusion:Undergraduate nursing interns experience significant perceived stress and a strong sense of job burnout.Their subjective well-being is correlated with their perceived stress and job burnout.It is necessary to optimize the clinical teaching model and provide psychological skills training to alleviate the interns’perceived stress and job burnout,thereby significantly enhancing their subjective well-being.展开更多
Basal melting and calving are the main pathways for mass loss in Antarctic ice shelves.Basal channels,as detailed variations in basal melting,mutually promote basal melting and calving,thereby weakening the stability ...Basal melting and calving are the main pathways for mass loss in Antarctic ice shelves.Basal channels,as detailed variations in basal melting,mutually promote basal melting and calving,thereby weakening the stability of ice shelves.Therefore,it is necessary to calculate and statistically analyze basal melting,basal channels,and calving events across all Antarctic ice shelves and examine the correlation among these three factors.This study utilizes various data sources to calculate the Basal Channel Density(BCD)and average basal melt rate of all Antarctic ice shelves during 2010-2020,as well as the spatial correlation between basal melting,basal channels,and calving.We found that ice shelves along the Amundsen Sea and Bellingshausen Sea have higher basal melt rates and basal channel densities,while other sea areas have lower values.This is mainly influenced by seabed topography and Circumpolar Deep Water.Excluding(CDW)extreme calving events,there is a positive correlation among basal melting,basal channels,and calving in coastal ice shelves across different sea areas,with a correlation coefficient exceeding 0.67.This indicates that basal melting and basal channels are major factors causing ice shelf calving.Our results emphasize the importance of the impact of basal melting,basal channels,and calving on ice shelf stability,and they provide a significant reference for further research on ice shelf-ocean interactions.展开更多
Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance ...Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.展开更多
Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumpt...Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumption dynamics was taken as the research object.A multi-task learning(MTL)method for BFG forecasting was proposed,which integrated a coupling correlation coefficient(CCC)and an inverted transformer structure.The CCC method could enhance key information extraction by establishing relationships between multiple prediction targets and relevant factors,while MTL effectively captured the inherent correlations between BFG generation and consumption.Finally,a real-world case study was conducted to compare the proposed model with four benchmark models.Results indicated significant reductions in average mean absolute percentage error by 33.37%,achieving 1.92%,with a computational time of 76 s.The sensitivity analysis of hyperparameters such as learning rate,batch size,and units of the long short-term memory layer highlights the importance of hyperparameter tuning.展开更多
BACKGROUND The development of prostate cancer(PC)frequently intensifies negative emotional states,such as anxiety and depression,which compromise the effectiveness of radical surgery and reduce treatment adherence.In ...BACKGROUND The development of prostate cancer(PC)frequently intensifies negative emotional states,such as anxiety and depression,which compromise the effectiveness of radical surgery and reduce treatment adherence.In this study,we hypothesized that psychological resilience plays a crucial role in this process and explored its impact.AIM To investigate the association of resilience with anxiety and depression in patients with PC and to analyze the influencing factors.METHODS We selected 147 patients with PC who visited Qingdao Traditional Chinese Medicine Hospital from January 2022 to June 2024.The resilience scores of patients with PC were assessed using the Connor-Davidson Resilience Scale(CDRISC)from the tenacity,self-improvement,and optimism dimensions.Based on the total CD-RISC score,patients were categorized into groups A(total CD-RISC score>63 points,n=69)and B(total CD-RISC score≤63 points,n=78)for comparative analysis of anxiety[Hamilton Anxiety Rating Scale(HAMA)],depression[Hamilton Depression Rating Scale(HAMD)],sexual function[International Index of Erectile Function-5(IIEF-5)and Sexual Life Quality Questionnaire-Quality of Life(SLQQ-QOL)],and quality of life[the EORTC Core Quality of Life Question naire(QLQ-C30)].The association between CD-RISC and the above indicators was analyzed with Spearman correlation coefficients,and the influencing factors of resilience in patients with PC were identified with binary logistic regression.RESULTS Group A demonstrated statistically lower HAMA and HAMD scores and markedly higher scores of IIEF-5,SLQQQOL,and various QLQ-C30 aspects.Correlation analysis revealed that CD-RISC was significantly negatively correlated with HAMA and HAMD scores and significantly positively correlated with IIEF-5,SLQQ-QOL,and QLQ-C30 total scores.Binary logistic regression analysis revealed educational and per capita monthly household income levels as significant influencing factors of resilience in patients with PC.CONCLUSION Our results indicate a significant correlation of resilience with anxiety and depression in patients with PC.The milder the anxiety and depression emotions in patients,the higher their resilience.Further,assisting patients with PC to improve their educational and per capita monthly household income levels will help their resilience to some extent.展开更多
Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macro...Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.展开更多
The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of...The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.展开更多
Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'...Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.展开更多
In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the couplin...In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Objective:To evaluate the global,regional,and national burden and determinants of Acute Respiratory Infections(ARIs)among children and adolescents from 1990 to 2021.Methods:We analysed ARI mortality and disability-adj...Objective:To evaluate the global,regional,and national burden and determinants of Acute Respiratory Infections(ARIs)among children and adolescents from 1990 to 2021.Methods:We analysed ARI mortality and disability-adjusted life years(DALYs),stratified by age,sex,and economic development level based on data retrieved from the Global Burden of Disease study 2021.Decomposition and frontier analyses were employed to identify key drivers of burden variation and visualize potential reductions based on development levels.Results:Between 1990 and 2021,the global burden of ARIs showed a significant decline in both achievable age-standardized DALYs rate and age-standardized mortality rates(EAPC=-3.87 and-3.81,respectively).Different age groups and sex witnessed different levels of ARI burden,males experienced heavier burden than females and the 0-4 years-old group experienced heavier burden than other study age groups.Most of the 204 countries and territories experienced a downward trend of ARI burden,with slight increases observed only in Lesotho and Dominica.A negative correlation was found between the Socio-demographic Index and ARI burden.Decomposition analysis indicated that the significant decreases in deaths and DALYs were primarily driven by epidemiological changes.Conclusions:The global burden of ARIs among children and adolescents has declined over the past three decades,but substantial regional disparities persist.Targeted public health strategies are needed to address the continued ARI burden in high-risk regions and vulnerable age groups.展开更多
The detection and characterization of non-metallic inclusions are essential for clean steel production.Recently,imaging analysis combined with high-dimensional data processing of metallic materials using artificial in...The detection and characterization of non-metallic inclusions are essential for clean steel production.Recently,imaging analysis combined with high-dimensional data processing of metallic materials using artificial intelligence(AI)-based machine learning(ML)has developed rapidly.This technique has achieved impressive results in the field of inclusion classification in process metallurgy.The present study surveys the ML modeling of inclusion prediction in advanced steels,including the detection,classification,and feature prediction of inclusions in different steel grades.Studies on clean steel with different features based on data and image analysis via ML are summarized.Regarding the data analysis,the inclusion prediction methodology based on ML establishes a connection between the experimental parameters and inclusion characteristics and analyzes the importance of the experimental parameters.Regarding the image analysis,the focus is placed on the classification of different types of inclusions via deep learning,in comparison with data analysis.Finally,further development of inclusion analyses using ML-based methods is recommended.This work paves the way for the application of AIbased methodologies for ultraclean-steel studies from a sustainable metallurgy perspective.展开更多
Red-fleshed fruits are valued for their vibrant color and high anthocyanin content.Pre-harvest fruit bagging enhances fruit peel pigmentation,but its effect on flesh coloration remains poorly characterized.This study ...Red-fleshed fruits are valued for their vibrant color and high anthocyanin content.Pre-harvest fruit bagging enhances fruit peel pigmentation,but its effect on flesh coloration remains poorly characterized.This study revealed that removing bags from‘Gengcunyangtao’red-fleshed peach fruits triggers the rapid and uniform accumulation of anthocyanins in the flesh,resulting in anthocyanin levels that exceed those in unbagged fruits.The exposure to light after bag removal triggered significant increases in anthocyanin levels within 24 h.This was accompanied by the rapid upregulation of light-responsive and flavonoid biosynthetic gene expression levels within 6 h.A metabolomic analysis indicated that anthocyanin precursors,especially p-coumaric acid,accumulated before bag removal,thereby increasing substrate availability for rapid anthocyanin synthesis.On the basis of a weighted gene co-expression network analysis,MYB transcription factors,anthocyanin transporters,glutathione S-transferase,and multidrug and toxic compound extrusion(MATE)were identified as key regulators that coordinate precursor storage along with light-induced transcriptional activation.Notably,PpMYB4 binds to the promoter of PpGSTF14 and activates its expression,thereby promoting anthocyanin accumulation.The study findings elucidated the temporal coordination of metabolic priming and light-responsive transcriptional regulation driving rapid anthocyanin biosynthesis,with possible implications for improving peach fruit flesh coloration.展开更多
BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM ...BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM To explore the correlations among life satisfaction,pleasure levels,and negative emotions in patients with CRF.METHODS One hundred patients with CRF who received therapy at the First Affiliated Hospital of Jinzhou Medical University between December 2022 and February 2025 were included.The Depression,Anxiety,and Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Temporal Experience of Pleasure Scale(TEPS)were used to evaluate negative emotions,life satisfaction,and pleasure level,respectively.Pearson’s correlation coefficient analyzed the correlation between life satisfaction,pleasure level,and negative emotions.Linear regression analysis identified the factors affecting negative emotions.RESULTS The average DASS-21 score among patients with CRF was 51.90±2.30,with subscale scores of 17.90±1.50 for depression,18.53±1.18 for anxiety,and 15.47±2.36 for stress,all significantly higher than the domestic norm(P<0.05).The average SWLS score was 22.17±4.90.Correlation analysis revealed a negative correlation between the SWLS and total DASS-21 scores(P<0.05),but not with the individual depression,anxiety,or stress dimensions.The average TEPS score was 67.80±8.34.TEPS scores were negatively correlated with the DASS-21 score and the stress dimension(P<0.05),but not with depression or anxiety.Linear regression analysis showed that TEPS scores significantly influenced DASS-21 scores(P<0.05).CONCLUSION Patients with CRF experience high levels of negative emotions,which are negatively correlated with life satisfaction and pleasure.Furthermore,pleasure level had an impact on negative emotions.展开更多
Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate em...Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate emergent phenomena such as enhanced energy transport.Here,we experimentally realize a 12-step discrete-time quantum walk in programmable integrated photonic circuits,introducing tunable static and dynamic disorder to explore quantum transport dynamics.In periodic lattices,disorder induces light localization and drives a transition from quantum ballistic to classical diffusive behavior.In particular,quantum walks of correlated photons exhibit a disorder-induced bunching effect,accompanied by enhanced nonclassical correlations.Our platform provides a scalable framework for investigating multiparticle quantum dynamics in engineered environments,promoting the development of quantum optics toward large-scale applications.展开更多
In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant ...In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant influence the correlation strength of the system.We investigate the impact of on-site inter-orbital hybridization on the correlation strength of a two-orbital Hubbard model on a square lattice using the dynamical mean-field theory combined with Lanczos exact diagonalization.Our findings reveal a distinct Janus effect:on-site inter-orbital hybridization enhances correlation strength in the non-half-filled regime while suppresses it at half-filling.This dual role of on-site inter-orbital hybridization provides a fundamental mechanism for tuning the strength of correlations in multi-orbital systems.展开更多
文摘Ensuring software quality in open⁃source environments requires adaptive mechanisms to enhance scalability,optimize service provisioning,and improve reliability.This study presents the dynamic correlation analysis technique to enhance software quality management in open⁃source environments by addressing dynamic scalability,adaptive service provisioning,and software reliability.The proposed methodology integrates a scalability metric,an optimized service provisioning model,and a weighted entropy⁃based reliability assessment to systematically improve key performance parameters.Experimental evaluation conducted on multiple open⁃source software(OSS)versions demonstrates significant improvements:scalability increased by 27.5%,service provisioning time reduced by 18.3%,and software reliability improved by 22.1%compared to baseline methods.A comparative analysis with prior works further highlights the effectiveness of this approach in ensuring adaptability,efficiency,and resilience in dynamic software ecosystems.Future work will focus on real⁃time monitoring and AI⁃driven adaptive provisioning to further enhance software quality management.
文摘BACKGROUND Psychological comorbidities,such as anxiety and depression,in patients with chronic ankle instability(CAI)may impede ankle function improvement,although the precise nature of this association warrants further investigation.AIM To analyze the correlation of anxiety and depression with ankle function in patients with CAI and discussing the risk factors.METHODS This study included 116 patients with CAI,who were admitted to our hospital from July 2022 to July 2024.Anxiety and depression states of patients were assessed with the self-rating anxiety scale(SAS)and self-rating depression scale(SDS),respectively,and their ankle joint function was assessed with the anklehindfoot function score of the American Orthopedic Foot and Ankle Society.Further,the ankle function of patients with CAI with different anxiety and depression states was discussed.Furthermore,the Pearson correlation coefficient was used to analyze the correlation of anxiety and depression with ankle joint function in such patients.Univariate and multivariate analyses were conducted to investigate the factors affecting ankle joint function in patients with CAI.RESULTS Among the 116 patients with CAI,97,13,5,and 1 cases demonstrated none,mild,moderate,and severe anxiety,whereas 95,15,6,and 0 cases showed none,mild,moderate,and severe depression,respectively.The average ankle joint function score was 74.82±6.93 points.The ankle joint function in patients with CAI presented a significant downward tendency as the degree of anxiety and depression increased.Correlation analysis revealed that both the SAS and SDS scores of patients with CAI were significantly negatively correlated with the ankle joint function score.Univariate and multivariate analyses indicated that the risk factors affecting patients’ankle joint function included early functional rehabilitation,visual analog scale,and SDS.CONCLUSION A substantial number of patients with CAI suffer from anxiety and depression,and these negative emotions,to a certain extent,harm the smooth rehabilitation of ankle joint function.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
基金National Natural Science Foundation of China(Project No.:12201579)。
文摘Portfolio selection based on the global minimum variance(GMV)model remains a significant focus in financial research.The covariance matrix,central to the GMV model,determines portfolio weights,and its accurate estimation is key to effective strategies.Based on the decomposition form of the covariance matrix.This paper introduces semi-variance for improved financial asymmetric risk measurement;addresses asymmetry in financial asset correlations using distance,asymmetric,and Chatterjee correlations to refine covariance matrices;and proposes three new covariance matrix models to enhance risk assessment and portfolio selection strategies.Testing with data from 30 stocks across various sectors of the Chinese market confirms the strong performance of the proposed strategies.
文摘Objective:To analyze the correlation between perceived stress,job burnout,and subjective well-being among undergraduate nursing interns.Methods:A total of 260 clinical nursing interns who interned in tertiary hospitals from July 2024 to April 2025 were selected as the survey subjects.They were administered the Chinese version of the Perceived Stress Scale(CPSS),the Maslach Burnout Inventory-Human Services Survey(MBI-HSS),and the General Well-being Schedule(GWB)to evaluate the correlation between perceived stress,job burnout,and subjective well-being.Results:The subjective well-being scores of those with higher perceived stress were lower than those with moderate stress;individuals with severe job burnout had lower subjective well-being compared to those without job burnout or with mild to moderate job burnout levels(p<0.05).Correlation analysis revealed that the subjective well-being of undergraduate nursing interns was negatively correlated with perceived stress and job burnout(p<0.05).Conclusion:Undergraduate nursing interns experience significant perceived stress and a strong sense of job burnout.Their subjective well-being is correlated with their perceived stress and job burnout.It is necessary to optimize the clinical teaching model and provide psychological skills training to alleviate the interns’perceived stress and job burnout,thereby significantly enhancing their subjective well-being.
基金The National Natural Science Foundation of China No.42406251the Fundamental Research Funds for the Central Universities under contract No.2042025kf0079 and 2042025kf0080+2 种基金the Postdoctoral Fellowship Program of CPSF under contract No.GZC20241257the Postdoctoral Fellowship Program of CPSF under contract No.GZC20241257the Key Laboratory of Polar Environment Monitoring and Public Governance(Wuhan University),the Ministry of Education Open Fund under contract Nos 202403 and 202405.
文摘Basal melting and calving are the main pathways for mass loss in Antarctic ice shelves.Basal channels,as detailed variations in basal melting,mutually promote basal melting and calving,thereby weakening the stability of ice shelves.Therefore,it is necessary to calculate and statistically analyze basal melting,basal channels,and calving events across all Antarctic ice shelves and examine the correlation among these three factors.This study utilizes various data sources to calculate the Basal Channel Density(BCD)and average basal melt rate of all Antarctic ice shelves during 2010-2020,as well as the spatial correlation between basal melting,basal channels,and calving.We found that ice shelves along the Amundsen Sea and Bellingshausen Sea have higher basal melt rates and basal channel densities,while other sea areas have lower values.This is mainly influenced by seabed topography and Circumpolar Deep Water.Excluding(CDW)extreme calving events,there is a positive correlation among basal melting,basal channels,and calving in coastal ice shelves across different sea areas,with a correlation coefficient exceeding 0.67.This indicates that basal melting and basal channels are major factors causing ice shelf calving.Our results emphasize the importance of the impact of basal melting,basal channels,and calving on ice shelf stability,and they provide a significant reference for further research on ice shelf-ocean interactions.
基金supported in part by the National Natural Science Foundation of China under Grants NO.61971161 and 62171151in part by the Foundation of Heilongjiang Touyan Team under Grant NO.HITTY-20190009+3 种基金and in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2021012supported in part by the Natural Science Foundation of China under Grant NO.62171160in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2022055in part by the Shenzhen Science and Technology Program under Grants NO.JCYJ20190806143212658 and ZDSYS20210623091808025.
文摘Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.
基金supported by the National Natural Science Foundation of China(No.52474435)China Baowu Low Carbon Metallurgy Innovation Foundation(BWLCF202307).
文摘Accurate forecasting of blast furnace gas(BFG)production is an essential prerequisite for reasonable energy scheduling and management to reduce carbon emissions.Coupling forecasting between BFG generation and consumption dynamics was taken as the research object.A multi-task learning(MTL)method for BFG forecasting was proposed,which integrated a coupling correlation coefficient(CCC)and an inverted transformer structure.The CCC method could enhance key information extraction by establishing relationships between multiple prediction targets and relevant factors,while MTL effectively captured the inherent correlations between BFG generation and consumption.Finally,a real-world case study was conducted to compare the proposed model with four benchmark models.Results indicated significant reductions in average mean absolute percentage error by 33.37%,achieving 1.92%,with a computational time of 76 s.The sensitivity analysis of hyperparameters such as learning rate,batch size,and units of the long short-term memory layer highlights the importance of hyperparameter tuning.
文摘BACKGROUND The development of prostate cancer(PC)frequently intensifies negative emotional states,such as anxiety and depression,which compromise the effectiveness of radical surgery and reduce treatment adherence.In this study,we hypothesized that psychological resilience plays a crucial role in this process and explored its impact.AIM To investigate the association of resilience with anxiety and depression in patients with PC and to analyze the influencing factors.METHODS We selected 147 patients with PC who visited Qingdao Traditional Chinese Medicine Hospital from January 2022 to June 2024.The resilience scores of patients with PC were assessed using the Connor-Davidson Resilience Scale(CDRISC)from the tenacity,self-improvement,and optimism dimensions.Based on the total CD-RISC score,patients were categorized into groups A(total CD-RISC score>63 points,n=69)and B(total CD-RISC score≤63 points,n=78)for comparative analysis of anxiety[Hamilton Anxiety Rating Scale(HAMA)],depression[Hamilton Depression Rating Scale(HAMD)],sexual function[International Index of Erectile Function-5(IIEF-5)and Sexual Life Quality Questionnaire-Quality of Life(SLQQ-QOL)],and quality of life[the EORTC Core Quality of Life Question naire(QLQ-C30)].The association between CD-RISC and the above indicators was analyzed with Spearman correlation coefficients,and the influencing factors of resilience in patients with PC were identified with binary logistic regression.RESULTS Group A demonstrated statistically lower HAMA and HAMD scores and markedly higher scores of IIEF-5,SLQQQOL,and various QLQ-C30 aspects.Correlation analysis revealed that CD-RISC was significantly negatively correlated with HAMA and HAMD scores and significantly positively correlated with IIEF-5,SLQQ-QOL,and QLQ-C30 total scores.Binary logistic regression analysis revealed educational and per capita monthly household income levels as significant influencing factors of resilience in patients with PC.CONCLUSION Our results indicate a significant correlation of resilience with anxiety and depression in patients with PC.The milder the anxiety and depression emotions in patients,the higher their resilience.Further,assisting patients with PC to improve their educational and per capita monthly household income levels will help their resilience to some extent.
基金supported by Qingdao Key Medical and Health Discipline ProjectThe Intramural Research Program of the Affiliated Hospital of Qingdao University,No. 4910Qingdao West Coast New Area Science and Technology Project,No. 2020-55 (all to SW)。
文摘Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment.
文摘The efficient market hypothesis in traditional financial theory struggles to explain the short-term irrational fluctuations in the A-share market,where investor sentiment fluctuations often serve as the core driver of abnormal stock price movements.Traditional sentiment measurement methods suffer from limitations such as lag,high misjudgment rates,and the inability to distinguish confounding factors.To more accurately explore the dynamic correlation between investor sentiment and stock price fluctuations,this paper proposes a sentiment analysis framework based on large language models(LLMs).By constructing continuous sentiment scoring factors and integrating them with a long short-term memory(LSTM)deep learning model,we analyze the correlation between investor sentiment and stock price fluctuations.Empirical results indicate that sentiment factors based on large language models can generate an annualized excess return of 9.3%in the CSI 500 index domain.The LSTM stock price prediction model incorporating sentiment features achieves a mean absolute percentage error(MAPE)as low as 2.72%,significantly outperforming traditional models.Through this analysis,we aim to provide quantitative references for optimizing investment decisions and preventing market risks.
文摘Six new lanthanide complexes:[Ln(3,4-DEOBA)3(4,4'-DM-2,2'-bipy)]2·2C_(2)H_(5)OH,[Ln=Dy(1),Eu(2),Tb(3),Sm(4),Ho(5),Gd(6);3,4-DEOBA-=3,4-diethoxybenzoate,4,4'-DM-2,2'-bipy=4,4'-dimethyl-2,2'-bipyridine]were successfully synthesized by the volatilization of the solution at room temperature.The crystal structures of six complexes were determined by single-crystal X-ray diffraction technology.The results showed that the complexes all have a binuclear structure,and the structures contain free ethanol molecules.Moreover,the coordination number of the central metal of each structural unit is eight.Adjacent structural units interact with each other through hydrogen bonds and further expand to form 1D chain-like and 2D planar structures.After conducting a systematic study on the luminescence properties of complexes 1-4,their emission and excitation spectra were obtained.Experimental results indicated that the fluorescence lifetimes of complexes 2 and 3 were 0.807 and 0.845 ms,respectively.The emission spectral data of complexes 1-4 were imported into the CIE chromaticity coordinate system,and their corre sponding luminescent regions cover the yellow light,red light,green light,and orange-red light bands,respectively.Within the temperature range of 299.15-1300 K,the thermal decomposition processes of the six complexes were comprehensively analyzed by using TG-DSC/FTIR/MS technology.The hypothesis of the gradual loss of ligand groups during the decomposition process was verified by detecting the escaped gas,3D infrared spectroscopy,and ion fragment information detected by mass spectrometry.The specific decomposition path is as follows:firstly,free ethanol molecules and neutral ligands are removed,and finally,acidic ligands are released;the final product is the corresponding metal oxide.CCDC:2430420,1;2430422,2;2430419,3;2430424,4;2430421,5;2430423,6.
基金supported by the Natural Science Foundation of Shanxi Province(Grant No.20210302124437)the Graduate Student Research and Innovation Project of Shanxi Province(Grant No.2023KY551).
文摘In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Objective:To evaluate the global,regional,and national burden and determinants of Acute Respiratory Infections(ARIs)among children and adolescents from 1990 to 2021.Methods:We analysed ARI mortality and disability-adjusted life years(DALYs),stratified by age,sex,and economic development level based on data retrieved from the Global Burden of Disease study 2021.Decomposition and frontier analyses were employed to identify key drivers of burden variation and visualize potential reductions based on development levels.Results:Between 1990 and 2021,the global burden of ARIs showed a significant decline in both achievable age-standardized DALYs rate and age-standardized mortality rates(EAPC=-3.87 and-3.81,respectively).Different age groups and sex witnessed different levels of ARI burden,males experienced heavier burden than females and the 0-4 years-old group experienced heavier burden than other study age groups.Most of the 204 countries and territories experienced a downward trend of ARI burden,with slight increases observed only in Lesotho and Dominica.A negative correlation was found between the Socio-demographic Index and ARI burden.Decomposition analysis indicated that the significant decreases in deaths and DALYs were primarily driven by epidemiological changes.Conclusions:The global burden of ARIs among children and adolescents has declined over the past three decades,but substantial regional disparities persist.Targeted public health strategies are needed to address the continued ARI burden in high-risk regions and vulnerable age groups.
基金support from the National Key Research and Development Program of China(No.2024YFB3713705)is acknowledgedWangzhong Mu would like to acknowledge the Strategic Mobility,Sweden(SSF,No.SM22-0039)+1 种基金the Swedish Foundation for International Cooperation in Research and Higher Education(STINT,No.IB2022-9228)the Jernkontoret(Sweden)for supporting this clean steel research.Gonghao Lian would like to acknowledge China Scholarship Council(CSC,No.202306080032).
文摘The detection and characterization of non-metallic inclusions are essential for clean steel production.Recently,imaging analysis combined with high-dimensional data processing of metallic materials using artificial intelligence(AI)-based machine learning(ML)has developed rapidly.This technique has achieved impressive results in the field of inclusion classification in process metallurgy.The present study surveys the ML modeling of inclusion prediction in advanced steels,including the detection,classification,and feature prediction of inclusions in different steel grades.Studies on clean steel with different features based on data and image analysis via ML are summarized.Regarding the data analysis,the inclusion prediction methodology based on ML establishes a connection between the experimental parameters and inclusion characteristics and analyzes the importance of the experimental parameters.Regarding the image analysis,the focus is placed on the classification of different types of inclusions via deep learning,in comparison with data analysis.Finally,further development of inclusion analyses using ML-based methods is recommended.This work paves the way for the application of AIbased methodologies for ultraclean-steel studies from a sustainable metallurgy perspective.
基金supported by the Key Scientific and Technological Grant of Zhejiang for Breeding New Agricultural Varieties(Grant No.2021C12066-4)Huzhou Agricultural Science and Technology Innovation Team Project(Grant No.2022HN01).
文摘Red-fleshed fruits are valued for their vibrant color and high anthocyanin content.Pre-harvest fruit bagging enhances fruit peel pigmentation,but its effect on flesh coloration remains poorly characterized.This study revealed that removing bags from‘Gengcunyangtao’red-fleshed peach fruits triggers the rapid and uniform accumulation of anthocyanins in the flesh,resulting in anthocyanin levels that exceed those in unbagged fruits.The exposure to light after bag removal triggered significant increases in anthocyanin levels within 24 h.This was accompanied by the rapid upregulation of light-responsive and flavonoid biosynthetic gene expression levels within 6 h.A metabolomic analysis indicated that anthocyanin precursors,especially p-coumaric acid,accumulated before bag removal,thereby increasing substrate availability for rapid anthocyanin synthesis.On the basis of a weighted gene co-expression network analysis,MYB transcription factors,anthocyanin transporters,glutathione S-transferase,and multidrug and toxic compound extrusion(MATE)were identified as key regulators that coordinate precursor storage along with light-induced transcriptional activation.Notably,PpMYB4 binds to the promoter of PpGSTF14 and activates its expression,thereby promoting anthocyanin accumulation.The study findings elucidated the temporal coordination of metabolic priming and light-responsive transcriptional regulation driving rapid anthocyanin biosynthesis,with possible implications for improving peach fruit flesh coloration.
文摘BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM To explore the correlations among life satisfaction,pleasure levels,and negative emotions in patients with CRF.METHODS One hundred patients with CRF who received therapy at the First Affiliated Hospital of Jinzhou Medical University between December 2022 and February 2025 were included.The Depression,Anxiety,and Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Temporal Experience of Pleasure Scale(TEPS)were used to evaluate negative emotions,life satisfaction,and pleasure level,respectively.Pearson’s correlation coefficient analyzed the correlation between life satisfaction,pleasure level,and negative emotions.Linear regression analysis identified the factors affecting negative emotions.RESULTS The average DASS-21 score among patients with CRF was 51.90±2.30,with subscale scores of 17.90±1.50 for depression,18.53±1.18 for anxiety,and 15.47±2.36 for stress,all significantly higher than the domestic norm(P<0.05).The average SWLS score was 22.17±4.90.Correlation analysis revealed a negative correlation between the SWLS and total DASS-21 scores(P<0.05),but not with the individual depression,anxiety,or stress dimensions.The average TEPS score was 67.80±8.34.TEPS scores were negatively correlated with the DASS-21 score and the stress dimension(P<0.05),but not with depression or anxiety.Linear regression analysis showed that TEPS scores significantly influenced DASS-21 scores(P<0.05).CONCLUSION Patients with CRF experience high levels of negative emotions,which are negatively correlated with life satisfaction and pleasure.Furthermore,pleasure level had an impact on negative emotions.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2325022,U23A2074,12204462,62275240,62435009,12474494,and 12204468)the Chinese Academy of Sciences(CAS)Project for Young Scientists in Basic Research(Grant No.253 YSBR-049)+3 种基金the Key Research and Development Program of Anhui Province(Grant No.2022b1302007)the China Postdoctoral Science Foundation(Grant No.2024M753083)the National Postdoctoral Program for Innovative Talents(Grant No.BX20240353)the Fundamental Research Funds for the Central Universities(Grant Nos.WK2030000107,WK2030000108,and WK2030000081)。
文摘Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate emergent phenomena such as enhanced energy transport.Here,we experimentally realize a 12-step discrete-time quantum walk in programmable integrated photonic circuits,introducing tunable static and dynamic disorder to explore quantum transport dynamics.In periodic lattices,disorder induces light localization and drives a transition from quantum ballistic to classical diffusive behavior.In particular,quantum walks of correlated photons exhibit a disorder-induced bunching effect,accompanied by enhanced nonclassical correlations.Our platform provides a scalable framework for investigating multiparticle quantum dynamics in engineered environments,promoting the development of quantum optics toward large-scale applications.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174327)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2023ZD09)。
文摘In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant influence the correlation strength of the system.We investigate the impact of on-site inter-orbital hybridization on the correlation strength of a two-orbital Hubbard model on a square lattice using the dynamical mean-field theory combined with Lanczos exact diagonalization.Our findings reveal a distinct Janus effect:on-site inter-orbital hybridization enhances correlation strength in the non-half-filled regime while suppresses it at half-filling.This dual role of on-site inter-orbital hybridization provides a fundamental mechanism for tuning the strength of correlations in multi-orbital systems.
